Evidence map›Paper›PMID 40238040›Full record

ReviewCurrent cardiology reports2025

Cardiac Magnetic Resonance Guidance for the Pathogenetic Definition of Cardiomyopathies.

Bishow Paudel, Jonathan Pan, Cristiane C Singulane, Shuo Wang, Matthew Thomas, Michael Ayers, Steven Philips, Amit R Patel

Abstract readReview
In one paragraph

Review in Current cardiology reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Review
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Bishow PaudelDepartment of Medicine, Division of Cardiovascular Medicine, University of Virginia, Charlottesville, VA, USA.
Jonathan PanDepartment of Medicine, Division of Cardiovascular Medicine, University of Virginia, Charlottesville, VA, USA.
Cristiane C SingulaneDepartment of Medicine, Division of Cardiovascular Medicine, University of Virginia, Charlottesville, VA, USA.
Shuo WangDepartment of Medicine, Division of Cardiovascular Medicine, University of Virginia, Charlottesville, VA, USA.
Matthew ThomasDepartment of Medicine, Division of Cardiovascular Medicine, University of Virginia, Charlottesville, VA, USA.
Michael AyersDepartment of Medicine, Division of Cardiovascular Medicine, University of Virginia, Charlottesville, VA, USA.
Steven PhilipsDepartment of Medicine, Division of Cardiovascular Medicine, University of Virginia, Charlottesville, VA, USA.
Amit R PatelDepartment of Medicine, Division of Cardiovascular Medicine, University of Virginia, Charlottesville, VA, USA. apatel@virginia.edu.

Funding

Training in Cardiovascular Imaging ResearchT32EB003841 · NIBIB · UNIVERSITY OF VIRGINIA CHARLOTTESVILLE · PI Jonathan R Lindner · 2004 to 2026
$4.4M
NIBIB NIH HHS T32 EB003841NIH HHS T32EB003841
6 · The paper itself

Abstract

purpose of reviewPathogenetics is the study of genetics in disease pathogenesis. Many abnormal gene alleles have been identified in cardiomyopathies, but their clinical utility remains limited. This review aims to examine the integration of cardiac MRI (CMR) with genetic data to enhance early detection, prognostication, and treatment strategies for cardiomyopathies. RECENT

findingsCMR is the gold standard imaging modality for cardiomyopathy evaluation, capable of detecting subtle structural and functional changes throughout the disease course. When applied to patients with genetic mutations, with or without phenotypic expression, CMR aids in early diagnosis and risk stratification. Cardiomyopathies can be categorized into at least seven clinical groups based on morphology, function, and genetic associations: (1) Dilated cardiomyopathy (DCM), (2) Hypertrophic cardiomyopathy (HCM), (3) Restrictive cardiomyopathy, including transthyretin amyloidosis (ATTR-CM), iron overload, and Anderson-Fabry disease, (4) Arrhythmogenic cardiomyopathy (ACM), (5) Non-dilated left ventricular cardiomyopathy (NDLVC), (6) Peripartum cardiomyopathy, and (7) Muscular dystrophy-related cardiomyopathy. We have described left ventricular noncompaction (LVNC) as a morphological trait rather than a distinct cardiomyopathy. Emerging CMR and genetic data suggest an inflammatory component in DCM and ACM, with potential therapeutic implications for immunotherapy. Advanced CMR techniques, such as quantitative perfusion, can distinguish cardiomyopathies from ischemic heart disease and detect early microvascular dysfunction, particularly in ATTR-CM and HCM. Late gadolinium enhancement (LGE) and parametric mapping (T1 and extracellular volume [ECV]) further enhance early diagnosis, prognostication and treatment response by assessing fibrosis and myocardial composition. The integration of CMR and genetic insights improves our understanding of cardiomyopathy pathogenesis, aiding in early diagnosis and prognostic assessment. Future research should leverage artificial intelligence (AI) to analyze genetic and radiomic CMR features, including perfusion data, to establish a comprehensive pathogenetic framework. This approach could refine disease classification, identify novel therapeutic targets, and advance precision medicine in cardiomyopathy management.

Indexed as

CardiomyopathiesMagnetic Resonance ImagingMagnetic Resonance Imaging, CineCardiomyopathy, HypertrophicHumansPrognosisCardiac Magnetic Resonance (CMR) FeaturesCMR-pathogeneticGenesGenetic/Inherited cardiomyopathyInflammation

Identifiers

PMID40238040
PMCPMC12003507

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.